Epilepsy and epilepsy-related behaviour disorders among people with intellectual disability

2012 ◽  
pp. 1860-1870
Author(s):  
Matti Iivanainen
Keyword(s):  
Intellectual Disability ◽  
Antiepileptic Drugs ◽  
Epileptic Seizure ◽  
Stable Condition ◽  
Epileptic Seizures ◽  
Epileptic Syndrome ◽  
Short Period ◽  
Eeg Changes ◽  
The Brain ◽  
Symptoms And Signs

Epilepsy is defined as at least one epileptic seizure; this in practice means two or more epileptic seizures unprovoked by any immediate identifiable cause during a relatively short period of time. Epileptic seizure is a clinical manifestation presumed to result from an abnormal and excessive discharge of a set of neurones in the brain. An epileptic syndrome is a cluster of symptoms and signs including type of seizure, mode of seizure recurrence, neurological findings, and neuroradiological or other findings of special investigations, customarily occurring together. An epileptic syndrome can have more than one cause or the cause may remain unknown; consequently outcomes may be different. Pseudoseizure is used to denote epilepsy-like seizures without concomitant EEG changes. Epilepsy and intellectual disability are symptoms of brain origin. The former is an unstable condition, where during the seizure or ictally the behaviour of a person with epilepsy is abnormal, but between the seizures or interictally there is no affect of epilepsy on his or her behaviour. Intellectual disability is a more or less stable condition. However, the categories of the degrees of intellectual disability are neither absolute nor static, as some children may move up or down between them. This chapter deals with the diagnosis, manifestations, behavioural disorders, frequency, aetiology, treatment, effects of antiepileptic drugs on behaviour, and prognosis of epilepsy in people with intellectual disability.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

Epilepsy in later childhood and adulthood

2010 ◽  
pp. 4810-4826
Author(s):  
G.D. Perkin ◽  
M.R. Johnson
Keyword(s):  
Brain Imaging ◽  
Neuronal Activity ◽  
Case History ◽  
Epileptic Seizure ◽  
Neurological Disease ◽  
Epileptic Seizures ◽  
Social Consequences ◽  
Definition Of ◽  
The Brain ◽  
Structural Brain

Case History—A 33 yr old woman, known to have epilepsy, now presenting with odd behaviour. An epileptic seizure is a transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain. Epilepsy is defined as a disorder of the brain characterized by an enduring predisposition to generate epileptic seizures and by the neurobiological, cognitive, psychological, and social consequences of this condition. The definition of epilepsy requires the occurrence of at least one epileptic seizure and evidence for an enduring alteration in the brain that increases the likelihood of future seizures such as an ‘epileptiform’ EEG abnormality, an appropriate lesion on structural brain imaging (CT or MRI), or the presence of recurrent (two or more) seizures. Epilepsy is a common, serious neurological disease, with prevalence 1% and a cumulative lifetime risk of 5%....

scholarly journals The fence post depth electrode technique to control both brain tumors and epileptic seizures in patients with brain tumor-related epilepsy

2019 ◽  
Vol 10 ◽  
pp. 187 ◽  
Author(s):  
Yosuke Masuda ◽  
Ayataka Fujimoto ◽  
Mitsuyo Nishimura ◽  
Keishiro Sato ◽  
Hideo Enoki ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Epileptic Seizure ◽  
Epileptic Seizures ◽  
Seizure Onset ◽  
Tumor Removal ◽  
Depth Electrodes ◽  
Fence Post ◽  
Group 2 ◽  
The Brain ◽  
Group 1

Background: To control brain tumor-related epilepsy (BTRE), both epileptological and neuro-oncological approaches are required. We hypothesized that using depth electrodes (DEs) as fence post catheters, we could detect the area of epileptic seizure onset and achieve both brain tumor removal and epileptic seizure control. Methods: Between August 2009 and April 2018, we performed brain tumor removal for 27 patients with BTRE. Patients who underwent lesionectomy without DEs were classified into Group 1 (13 patients) and patients who underwent the fence post DE technique were classified into Group 2 (14 patients). Results: The patients were 15 women and 12 men (mean age, 28.1 years; median age 21 years; range, 5–68 years). The brain tumor was resected to a greater extent in Group 2 than Group 1 (P < 0.001). Shallower contacts showed more epileptogenicity than deeper contacts (P < 0.001). Group 2 showed better epilepsy surgical outcomes than Group 1 (P = 0.041). Conclusion: Using DEs as fence post catheters, we detected the area of epileptic seizure onset and controlled epileptic seizures. Simultaneously, we removed the brain tumor to a greater extent with fence post DEs than without.

Comparative investigation of machine learning algorithms for detection of epileptic seizures

2021 ◽  
pp. 1-11
Author(s):  
Akash Sharma ◽  
Neeraj Kumar ◽  
Ayush Kumar ◽  
Karan Dikshit ◽  
Kusum Tharani ◽  
...  
Keyword(s):  
Epileptic Seizure ◽  
Preventive Treatment ◽  
Epileptic Seizures ◽  
Comparative Investigation ◽  
Machine Learning Algorithms ◽  
Average Value ◽  
Prediction Time ◽  
The Right ◽  
Electroencephalogram Eeg ◽  
The Brain

In modern day Psychiatric analysis, Epileptic Seizures are considered as one of the most dreadful disorders of the human brain that drastically affects the neurological activity of the brain for a short duration of time. Thus, seizure detection before its actual occurrence is quintessential to ensure that the right kind of preventive treatment is given to the patient. The predictive analysis is carried out in the preictal state of the Epileptic Seizure that corresponds to the state that commences a couple of minutes before the onset of the seizure. In this paper, the average value of prediction time is restricted to 23.4 minutes for a total of 23 subjects. This paper intends to compare the accuracy of three different predictive models, namely – Logistic Regression, Decision Trees and XGBoost Classifier based on the study of Electroencephalogram (EEG) signals and determine which model has the highest rate of detection of Epileptic Seizure.

scholarly journals The State of the Art in Feature Extraction Methods for EEG Classification

2019 ◽  
Vol 3 (2) ◽  
pp. 16
Author(s):  
Hoger Mahmud Hussen
Keyword(s):  
Epileptic Seizure ◽  
Neurological Disease ◽  
State Of The Art ◽  
Epileptic Seizures ◽  
Extraction Methods ◽  
Eeg Classification ◽  
The World ◽  
Electroencephalogram Eeg ◽  
The Brain ◽  
Eeg Features

Epileptic seizure is a neurological disease that is common around the world and there are many types (e.g. Focal aware seizures and atonic seizure) that are caused by synchronous or abnormal neuronal activity in the brain. A number of techniques are available to detect the brain activities that lead to Epileptic seizures; one of the most common one is Electroencephalogram (EEG) that uses visual scanning to measure brain activities generated by nerve cells in the cerebral cortex. The techniques make use of different features detected by EEG to decide on the occurrence and type of seizures. In this paper we review EEG features proposed by different researches for the purpose of Epileptic seizure detection, also analyze, and compare the performance of the proposed features.

Epilepsy in later childhood and adulthood

2020 ◽  
pp. 5860-5882
Author(s):  
Arjune Sen ◽  
M.R. Johnson
Keyword(s):  
Neuronal Activity ◽  
Epileptic Seizure ◽  
Neurological Disease ◽  
Epileptic Seizures ◽  
Social Consequences ◽  
Clinical Event ◽  
Unprovoked Seizure ◽  
Definition Of ◽  
The Brain ◽  
Structural Brain

Epilepsy is a common, serious neurological disease, with prevalence of 1% and a cumulative lifetime risk of 5%. An epileptic seizure is a transient occurrence of signs and/or symptoms due to abnormal excessive, synchronous neuronal activity. Epilepsy is defined as a disorder of the brain characterized by an enduring predisposition to generate epileptic seizures and by the neurobiological, cognitive, psychological, and social consequences of this condition. Traditionally epilepsy was diagnosed after a patient had two or more unprovoked seizures. However, a more modern definition of epilepsy would also include patients who have had an isolated seizure and have evidence for an enduring alteration in the brain that increases the likelihood of future seizures such as an ‘epileptiform’ electroencephalogram abnormality or an appropriate lesion on structural brain imaging (CT or MRI). Epilepsy cannot, though, be diagnosed unless there has been at least one clinical event compatible with an unprovoked seizure.

Listening to people with seizures: How can linguistic analysis help in the differential diagnosis of seizure disorders?

2008 ◽  
Vol 5 (1) ◽  
pp. 59-72 ◽  
Author(s):  
Meike Schwabe ◽  
Markus Reuber ◽  
Martin Schöndienst ◽  
Elisabeth Gülich
Keyword(s):  
Differential Diagnosis ◽  
Antiepileptic Drugs ◽  
Epileptic Seizure ◽  
Medical Technology ◽  
Epileptic Seizures ◽  
Linguistic Analysis ◽  
Multidisciplinary Research ◽  
Seizure Disorders ◽  
The University ◽  
Interactional Features

Despite advances in medical technology, the patients’ history remains the most crucial tool in the differential diagnosis of epileptic or non-epileptic seizures (NES). The distinction of these two types of seizures is a common and important task for neurologists. Whereas epileptic seizures would be treated with antiepileptic drugs, non-epileptic seizures are thought to be a manifestation of psychological or social distress and can improve with psychotherapy. This paper summarizes the findings of a series of multidisciplinary research studies undertaken at the Bethel Epilepsy Centre and the University of Bielefeld in Germany in which linguistic analysis was carried out to identify and describe linguistic and interactional features in clinical exchanges between doctors and patients with seizures. Two distinct communication profiles emerged in these studies based on the analysis of transcripts of over 110 doctor-patient encounters. Epileptic seizure descriptions are characterized by formulation effort, provide the doctor with a coherent account of individual seizures, relate subjective seizure experiences and use consistent metaphoric conceptualizations. Patients with NES tend not to volunteer subjective seizure symptoms, give accounts of their seizures which are difficult to understand and are inconsistent in their choice of metaphors.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

Severe Head Injury linked to Subsequent Development of Malignant Brain Tumour within a Short Period- A Case Report

2018 ◽  
Vol 3 (2) ◽  
Keyword(s):  
Head Injury ◽  
Brain Tumour ◽  
Severe Head Injury ◽  
Case Reports ◽  
Subsequent Development ◽  
Malignant Brain Tumour ◽  
Tumour Development ◽  
Short Period ◽  
The Brain

There have been a few case reports of head injury leading to brain tumour development in the same region as the brain injury. Here we report a case where the patient suffered a severe head injury with contusion. He recovered clinically with conservative management. Follow up Computed Tomography scan of the brain a month later showed complete resolution of the lesion. He subsequently developed malignant brain tumour in the same region as the original contusion within a very short period of 15 months. Head injury patients need close follow up especially when severe. The link between severity of head injury and malignant brain tumour development needs further evaluation. Role of anti-inflammatory agents for prevention of post traumatic brain tumours needs further exploration.

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